Leveraging formal languages and automata theory in natural language processing (NLP)

Journal of Discrete Mathematical Sciences and Cryptography 2026

View at publisher
Authors: Smita Gambhire, Archana R. Panhalkar, Dipali Himmatrao Patil, Seema Kedar, Malayaj Kumar, Brijeshkumar Y. Panchal
DOI: 10.47974/jdmsc-2552
Cited by: 1

Abstract

Formal languages and automata theory are very important for handling and understanding real languages. This paper discuss about basic automata models, such as finite automata and finite-state transducers, and how they can be used in morphological analysis, tokenization, and lexical analysis. The paper also focuses how these old techniques can be combined with natural language processing methods. In particular, it focusses on mixed models that use automata theory and machine learning to make things more accurate and quick. The part automata theory plays in formal checking and explaining NLP models is also looked at, shows how important it is for making systems that are clear and dependable.

Fields of Study & Subjects

Natural Language Processing Techniques Machine Learning and Algorithms Formal Methods in Verification

Publication details

Journal / source
Journal of Discrete Mathematical Sciences and Cryptography
Publisher
Taru Publications
Volume
29
Issue
2-B
Pages
995–1004
Publication date
1 January 2026